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KDD
2004
ACM
117views Data Mining» more  KDD 2004»
15 years 10 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
15 years 10 months ago
Machine learning for online query relaxation
In this paper we provide a fast, data-driven solution to the failing query problem: given a query that returns an empty answer, how can one relax the query's constraints so t...
Ion Muslea
AUSAI
2004
Springer
15 years 3 months ago
A Bayesian Metric for Evaluating Machine Learning Algorithms
How to assess the performance of machine learning algorithms is a problem of increasing interest and urgency as the data mining application of myriad algorithms grows. The standard...
Lucas R. Hope, Kevin B. Korb
KDD
2007
ACM
142views Data Mining» more  KDD 2007»
15 years 10 months ago
Towards Privacy-Preserving Model Selection
Abstract. Model selection is an important problem in statistics, machine learning, and data mining. In this paper, we investigate the problem of enabling multiple parties to perfor...
Zhiqiang Yang, Sheng Zhong, Rebecca N. Wright
COMSUR
2008
108views more  COMSUR 2008»
14 years 9 months ago
A survey of techniques for internet traffic classification using machine learning
The research community has begun looking for IP traffic classification techniques that do not rely on `well known' TCP or UDP port numbers, or interpreting the contents of pac...
Thuy T. T. Nguyen, Grenville J. Armitage